Facebook has sunk plans by Admiral to offer a reduced car insurance premium based on users posts on the social network.
That's exactly what Admiral wanted to do, using posts and likes to assess your personality and then determine whether you were a more conscientious driver or not.
“Protecting the privacy of the people on Facebook is of utmost importance to us. We have clear guidelines that prevent information being obtained from Facebook from being used to make decisions about eligibility," said Facebook in a statement.
“We have made sure anyone using this app is protected by our guidelines and that no Facebook user data is used to assess their eligibility. Facebook accounts will only be used for login and verification purposes. Our understanding is that Admiral will then ask users who sign up to answer questions which will be used to assess their eligibility.”
Earlier, Admiral had trumpeted the innovative new use of technology, saying: "There's a proven link between personality and how people drive, and our clever technology allows us to predict who is likely to be a safe driver."
Clear full sentences and being specific about dates when making plans when posting were said to be indicators of a good driver, with a discount of up to 15 per cent up for grabs to anyone sharing their profile information and deemed a good driver.
Now, Facebook has said this a breach of rules governing developers building apps on the platform after being alerted to it
It states: "Don't use data obtained from Facebook to make decisions about eligibility, including whether to approve or reject an application or how much interest to charge on a loan."
Using Facebook data provides a treasure trove of data from which much can be learned about people's behaviour, personality, and even credit worthiness. Facebook even landed a patent for assessing credit worthiness based on the score of friends and connections, though it doesn't appear to have done anything with it (yet, anyway).
However, in the US in particular, there has been some pullback on using the data due to implications such as regulation and also the unknown aspect of what kind of biases might be reproduced.